{"id":"W4249429000","doi":"10.1109/tnano.2016.2558262","title":"IEEE Transactions on Nanotechnology publication information","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Nanotechnology","topic":"Nanopore and Nanochannel Transport Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nanotechnology; Computer science; Data science; Materials science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001413412,0.0004632237,0.0004415043,0.001588155,0.0003756986,0.00002552004,0.0004251557,0.001013738,0.0002870713],"category_scores_gemma":[0.000008429814,0.00038404,0.0002189854,0.001100782,0.0002926616,0.000702569,6.025664e-7,0.0006428248,0.001186706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002783408,"about_ca_system_score_gemma":0.00004495506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001728558,"about_ca_topic_score_gemma":0.0000987129,"domain_scores_codex":[0.9979103,0.00002628349,0.0006831731,0.0004115037,0.000284994,0.0006837064],"domain_scores_gemma":[0.9987336,0.0001355392,0.0001039741,0.0007619406,0.0001677413,0.00009722877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001839383,0.0003314377,0.000002929673,0.00008441748,0.0003747633,0.00001133316,0.0002896672,0.01391309,0.1197323,0.001223923,0.001786647,0.8620656],"study_design_scores_gemma":[0.001342812,0.0004685584,0.000007271262,0.00008072762,0.00007837389,0.00004092817,0.00007487215,0.0008744405,0.9620202,0.0007051881,0.03378157,0.0005250259],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02824942,0.00006242641,0.9605788,0.004318202,0.002065536,0.0005108589,0.0002189344,0.003565701,0.0004300977],"genre_scores_gemma":[0.9965649,0.001446413,0.0005103812,0.0002782345,0.00003021661,0.0004970846,0.000006903268,0.00006616354,0.0005996823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9683155,"threshold_uncertainty_score":0.9998612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009563821592916128,"score_gpt":0.2009562303577806,"score_spread":0.1913924087648645,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}